systematic-debugging

Diagnose bugs through a four-phase root cause investigation process before proposing fixes.

Updated Sep 8, 2026
One-click install
npx skills add https://github.com/salomepoulain/makery-stations --skill systematic-debugging-salomepoulain
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/salomepoulain/makery-stations/tree/main/stations/claude/workbench/pantry/skills/systematic-debugging
Command: npx skills add https://github.com/salomepoulain/makery-stations --skill systematic-debugging-salomepoulain

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Developers often jump straight to fixes when facing bugs, test failures, or unexpected behavior, leading to symptom patches, repeated failed attempts, and wasted time. This Skill enforces a disciplined root-cause-first debugging methodology so fixes address the actual problem instead of its symptoms. ## Core Features & Use Cases - Four-Phase Debugging Process: Enforces root cause investigation, pattern analysis, hypothesis testing, and verified implementation in strict order. - Multi-Component Evidence Gathering: Provides diagnostic instrumentation patterns for tracing failures across layered systems like CI pipelines, build scripts, and signing steps. - Architectural Escalation: Detects when 3+ failed fixes indicate a fundamental design problem and prompts architectural review instead of more patching. - Use Case: When a CI build fails at the code-signing step, use this Skill to instrument each layer (workflow secrets, build environment, keychain state), identify exactly which boundary breaks, and fix the true source rather than guessing. ## Quick Start Use the systematic-debugging skill to investigate why my test suite is failing before suggesting any fixes.

Frequently Asked Questions about systematic-debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug a test failure systematically?

Start by reading error messages and stack traces completely, then reproduce the failure consistently and check recent changes via git diff. Form a single hypothesis, test it with the smallest possible change, and only implement a fix after confirming the root cause.

How to find root cause in multi-component systems?

Add diagnostic logging at each component boundary to capture what data enters and exits every layer. Run the system once to gather evidence showing exactly where the failure occurs, then investigate only that specific component instead of guessing.

When should I question the architecture instead of fixing a bug?

Question the architecture after three or more fix attempts have failed, especially when each fix reveals new problems in different places or requires massive refactoring. This pattern indicates a fundamental design issue rather than an isolated bug.

Why do quick fixes without investigation fail?

Quick fixes address symptoms rather than root causes, so the underlying problem resurfaces elsewhere. Untested fixes also cannot be verified, and bundling multiple changes makes it impossible to isolate what actually worked.

What should I do when a bug is not reproducible?

Do not guess when a bug cannot be reproduced consistently. Gather more data through logging and monitoring, document what you investigated, and add appropriate handling such as retries or timeouts for genuinely environmental issues.